The Design And Implement Of Monitoring System Of Network Public Opinion

Twenty years ago,just the rise of the computer network,after a decade has become a part of life,two years after it has been inseparable from the Internet today,and this virtual open platform.With recent changes in social networking model,paste it in the form of communication can not meet people's fast-paced life,people's social activities gradually changed to blog,micro blog and new social platforms.Due to the accelerated pace,people get information and they do not have much energy to distinguish between true and false information,which makes some false information to spread quickly.System Internet network public opinion is against the negative impact of a sharp knife,the information on the Internet can be monitored properly for some emergencies warning.Based on the study of domestic and abroad research status about the theory of public opinion,this thesis concentrates on the design of network monitoring system of public opinion and how to put it into practice in order to operate research work with the aim of enhancing traditional text mining applications in the system.This thesis has designed and carried out the following contents:Through analysis of the demand for network public opinion,to build an overall system framework for the network public opinion system,effectively solve problems referring to its structural design and system processes and verify its legitimacy and effectiveness by practice.By connection with related technologies at home and abroad,we will optimize the analysis and design of module respectively,completing a network monitoring system of public opinion with practical significance.To effectively improve the K-means clustering algorithm and put forward cohesion proposed k-means text clustering algorithm,starting with optimizing the text mining technology.Through the comparison between simulation examples and traditional algorithms,it is verified that the text cohesion k-means clustering algorithm has more effectiveness and superiority in analyzing information.